On testing for infections during epidemics, with application to Covid-19 in Ontario, Canada  

作　　者：Jerald F.Lawless Ping Yan 

机构地区：[1]Department of Statistics and Actuarial Science,University of Waterloo,Waterloo,ON,N2L 3G1,Canada [2]Public Health Agency of Canada,130 Colonnade Rd.,Ottawa,ON,K1A 0K9,Canada

出　　处：《Infectious Disease Modelling》2021年第1期930-941,共12页传染病建模（英文）

基　　金：Research was supported in part by Discovery Grant RGPIN-2017-04055 to JFL from the Natural Sciences and Engineering Research Council of Canada.

摘　　要：During an epidemic,accurate estimation of the numbers of viral infections in different regions and groups is important for understanding transmission and guiding public health actions.This depends on effective testing strategies that identify a high proportion of infections(that is,provide high ascertainment rates).For the novel coronavirus SARS-CoV-2,ascertainment rates do not appear to be high in most jurisdictions,but quantitative analysis of testing has been limited.We provide statistical models for studying testing and ascertainment rates,and illustrate them on public data on testing and case counts in Ontario,Canada.

关 键 词：Count data COVID-19 Modelling Testing strategies Ascertainment rate 

分 类 号：R563.1[医药卫生—呼吸系统] R18[医药卫生—内科学]